101 to 125 of 411 Pandas Jobs

to mentor colleagues, drive projects forward, and influence stakeholders. You should apply if you: Have a strong technical background, including proficiency in Python (NumPy, Pandas, Scikit-Learn, etc.), SQL, and cloud platforms such as GCP or AWS. Have experience working with modern databases like BigQuery, Snowflake, or Redshift. Have successfully More ❯

blend of some of the following skills: Machine learning techniques - including supervised and unsupervised methods and model evaluation. Key libraries including scikit-learn, scipy, pandas, and numpy (or equivalents). Data preprocessing - working with large untidy datasets and the ability to clean and transform data in preparation for analysis or More ❯

A/B testing, entity extraction, and feature engineering. Proficiency in programming languages such as Python, R, and SQL, and data analysis libraries (e.g., Pandas, NumPy, SciPy, Tidyverse). Strong knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, NLTK). Experience with NLP techniques, such as More ❯

e.g., R, Java, C++). Machine Learning & AI Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, or similar libraries. Data Manipulation & Analysis: Strong skills in Pandas, NumPy, and SQL for handling and analysing large datasets. Cloud Computing: Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for AI model More ❯

e.g., R, Java, C++). Machine Learning & AI Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, or similar libraries. Data Manipulation & Analysis: Strong skills in Pandas, NumPy, and SQL for handling and analysing large datasets. Cloud Computing: Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for AI model More ❯

control systems (e.g., Git). Strong expertise in Python, with a particular focus on libraries and tools commonly used in data engineering, such as Pandas, NumPy, Apache Airflow. Experience with data pipelines, ELT/ETL processes, and data wrangling. Dashboard analytics (PowerBI, Looker Studio or Tableau) experience. Excellent English, written More ❯

C/C++ Experience with machine learning pipelines and data science workflows. Knowledge of data warehousing concepts and tools. Familiarity with SQL Alchemy, Numpy, Pandas Hands-on experience with cloud services (AWS, GCP, Azure) for data engineering. Ability to troubleshoot and optimize complex data queries and workflows. Strong problem-solving More ❯

IT Experience IT qualification or relevant experience is desirable Proven experience with Python, SQL and desirably SOQL. Familiarity with a base set of libraries (Pandas, Numpy, Scikit-learn etc) Experience with Apex or Java A strong broad generalist background in working with computers and dealing with large amounts of information. More ❯

IT Experience IT qualification or relevant experience is desirable Proven experience with Python, SQL and desirably SOQL. Familiarity with a base set of libraries (Pandas, Numpy, Scikit-learn etc) Experience with Apex or Java A strong broad generalist background in working with computers and dealing with large amounts of information. More ❯

IT Experience IT qualification or relevant experience is desirable Proven experience with Python, SQL and desirably SOQL. Familiarity with a base set of libraries (Pandas, Numpy, Scikit-learn etc) Experience with Apex or Java A strong broad generalist background in working with computers and dealing with large amounts of information. More ❯

C# and Java Script (D3 or ChartJS) for web development. Knowledge of Cython, Numba, or Pybind11 for performance optimization. Familiarity with scientific computing (NumPy, Pandas, OpenCV). Knowledge of packaging and deployment tools (PyInstaller, Nuitka, cx_Freeze, or Briefcase). Familiarity with cross-platform development considerations. Understanding of security best More ❯

external GenAI models and platforms. Building reliable, scalable, and flexible systems. Influence Opinion and decision-making across AI and ML Skills Python SQL/Pandas/Snowflake/Elasticsearch Docker/Kubernetes Airflow/Spark Familiarity with GenAI models/libraries Requirements 4+ years of relevant data engineering experience post More ❯

external GenAI models and platforms. Building reliable, scalable, and flexible systems. Influence Opinion and decision-making across AI and ML Skills Python SQL/Pandas/Snowflake/Elasticsearch Docker/Kubernetes Airflow/Spark Familiarity with GenAI models/libraries Requirements 4+ years of relevant data engineering experience post More ❯

and project management tools and utilization of project management tools (e.g., JIRA). iv. Statistical, mathematical, and database Python packages (e.g., NumPy, SQLAlchemy, or Pandas More ❯

complex issues Beneficial experience • Experience in trading or execution roles • Experience with equity/credit markets • Research using large, messy datasets • Familiarity with Linux • Pandas Benefits: Working alongside other extremely talented and driven engineers Extremely lucrative salary, bonus and benefits More ❯

decisions. Key Responsibilities Develop and implement quantitative analytics for balance sheet and risk management Design and code models in Python using libraries such as Pandas and Numpy Work with Technology teams to operationalise analytics and ensure production readiness Ensure models comply with risk governance frameworks and policy standards Contribute to More ❯

decisions. Key Responsibilities Develop and implement quantitative analytics for balance sheet and risk management Design and code models in Python using libraries such as Pandas and Numpy Work with Technology teams to operationalise analytics and ensure production readiness Ensure models comply with risk governance frameworks and policy standards Contribute to More ❯

markets Experience with testing methodologies such as TDD (Test-Driven Development) and BDD (Behavior-Driven Development) Familiarity with technologies including PostgreSQL, Jenkins, Django, and Pandas Understanding of Microservices Architecture and development of RESTful API services Exposure to event-driven architectures, message queues, or event-streaming platforms Experience with cloud technologies More ❯

markets Experience with testing methodologies such as TDD (Test-Driven Development) and BDD (Behavior-Driven Development) Familiarity with technologies including PostgreSQL, Jenkins, Django, and Pandas Understanding of Microservices Architecture and development of RESTful API services Exposure to event-driven architectures, message queues, or event-streaming platforms Experience with cloud technologies More ❯

learning algorithms for text analytics Demonstrated experience with machine learning frameworks such as PyTorch, Keras, Tensorflow Demonstrated experience with data visualization tools (i.e. Tableau, Pandas, D3.js, ggplot, etc) Demonstrated experience with NoSQL data stores such as MongoDB or DynamoDB Demonstrated experience using Natural Language Processing tools such as spaCy, NLTK More ❯

problem-solving skills Technical: · Five years Python core development experience working in an enterprise environment. · Experience in creating libraries, restful services, websockets · Libraries: Polars, Pandas, AMPS, Asyncio, Threading, multiprocessing · Two years’ experience SQL Databases (PostGreSQL desirable) – preferred but not essential More ❯

problem-solving skills Technical: · Five years Python core development experience working in an enterprise environment. · Experience in creating libraries, restful services, websockets · Libraries: Polars, Pandas, AMPS, Asyncio, Threading, multiprocessing · Two years’ experience SQL Databases (PostGreSQL desirable) – preferred but not essential More ❯

data products. Tech Stack: Python - Core language for geospatial data processing Rasterio/GDAL - For handling and processing raster datasets xarray/NumPy/Pandas - For data manipulation and analysis AWS - For cloud-based data storage and processing PostGIS - For spatial data management (nice to have) What you'll be More ❯

data products. Tech Stack: Python - Core language for geospatial data processing Rasterio/GDAL - For handling and processing raster datasets xarray/NumPy/Pandas - For data manipulation and analysis AWS - For cloud-based data storage and processing PostGIS - For spatial data management (nice to have) What you'll be More ❯

Required Skills/Experience The ideal candidate will have the following: Experience in analytics or model/data engineering. Advanced Python skills (Numpy/Pandas). Strong SQL and relational database design expertise. Excellent communication skills. Benefits & Perks £6,000 per annum training & conference budget to help you up-skill More ❯